However, it is not an easy task to find general actionable rules for predicting the customers’ behavior, and directly use the rules provided by the results of the association rules could not solve the problem efficiently. In order to conquer this issue, we select different set of attributes from the derived association patterns
(as technique interestingness) and those consulted attributes (as business interestingness) for constructing decision trees.
At last,the each rule in the decision trees is then evaluated by the telecom providers for enhancing its predicting ability.
Finally, those verified rules are then collected as the operable business rule set (see
Section 3.4 for more details).